This repository contains a Python-based analytics pipeline for e-commerce data. It processes customer, product, and order data into clean tables, calculates daily KPIs, and checks for data quality and anomalies. The results are displayed in a Streamlit dashboard.
From the README
E-Commerce Modern Data Stack Pipeline What is this? This project builds a small analytics pipeline for e-commerce data. The goal is to turn raw customer, product and order data into clean tables that are easier to analyse. It also checks data quality and looks for unusual changes in revenue. Simple flow What it does • Processes customer data • Processes product data • Processes order data • Builds analytics tables • Calculates daily KPIs • Checks for missing/duplicate/invalid data • Detects unusual revenue changes • Shows results in a Streamlit dashboard Main files • seeddata.py — creates sample raw data • pipeline.py — runs the data pipeline • dataquality.py — checks data quality •...
Skills
- Python
